Table REF  compares the different anchor selection strategies, including random, \(k\) -means and farthestOriginally named as “Coverage” in [1]}. To avoid confusion, we rename this as “farthest”, as this method maximizes the distance across anchor users. [1]}. Although the difference in performance between the coverage-based selection and the other methods is not significant, the former consistently outperforms other selection methods. As reported in [1]}, the cluster-based selection shows a better performance than the random and farthest selection methods; however, it is less effective than the coverage-based selection. We conclude that the coverage-based selection effectively increases the number of local models, thereby obtaining consistent gains of LOCA.
